Effectiveness of antibacterial therapeutic clothing vs. nonantibacterial therapeutic clothing in patients with moderate-to-severe atopic dermatitis:a randomized controlled observer-blind pragmatic trial (ABC trial)

Background:Increased Staphylococcus aureus (SA) colonization is considered an important factor in the pathogenesis of atopic dermatitis (AD). Antibacterial therapeutic clothing aims to reduce SA colonization and AD inflammation; however, its role in the management of AD remains poorly understood. Objectives:To investigate the effectiveness of antibacterial therapeutic clothing+standard topical treatment in patients with moderate-to-severe AD vs. standard therapeutic clothing+standard topical treatment; and, if effectiveness was demonstrated, to demonstrate its cost-effectiveness. Methods:A pragmatic double-blinded multicentre randomized controlled trial (NCT04297215) was conducted in patients of all ages with moderate-to-severe AD. Patients were centrally randomized 1:1:1 to receive standard therapeutic clothing or antibacterial clothing based on chitosan or silver. The primary outcome was the between-group difference in Eczema Area and Severity Index (EASI) measured over 52 weeks. Secondary outcomes included patient-reported outcomes (PROs), topical corticosteroid (TCS) use, SA colonization, safety and cost-effectiveness. Outcomes were assessed by means of (generalized) linear mixed-model analyses. Results:Between 16 March 2020 and 20 December 2021, 171 patients were enrolled. In total, 159 patients were included (54 in the standard therapeutic clothing group, 50 in the chitosan group and 55 in the silver group). Adherence was high [median 7 nights a week wear (interquartile range 3–7)]. Median EASI scores at baseline and at 4, 12, 26 and 52 weeks were 11.8, 4.3, 4.6, 4.2 and 3.6, respectively, in the standard therapeutic clothing group vs. 11.3, 5.0, 3.0, 3.0 and 4.4, respectively, in the chitosan group, and 11.6, 5.0, 5.4, 4.6 and 5.8, respectively, in the silver group. No differences in EASI over 52 weeks between the standard therapeutic clothing group, the chitosan group [–0.1, 95% confidence interval (CI) –0.3 to 0.2; P=0.53] or the silver group (–0.1, 95% CI –0.3 to 0.2; P=0.58) were found. However, a small significant group×time interaction effect between the standard and silver groups was found (P=0.03), in which the silver group performed worse after 26 weeks. No differences between groups were found in PROs, TCS use, SA skin colonization and healthcare utilization. No severe adverse events or silver absorption were observed. Conclusions:The results of this study suggest no additional benefits of antibacterial agents in therapeutic clothing in patients with moderate-to-severe AD.</p

Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees

International audienceDusty, distant, massive ($M_*\gtrsim 10^{11}\,\rm M_\odot$) galaxies are usually found to show a remarkable star-formation activity, contributing on the order of $25\%$ of the cosmic star-formation rate density at $z\approx3$--$5$, and up to $30\%$ at $z\sim7$ from ALMA observations. Nonetheless, they are elusive in classical optical surveys, and current near-infrared surveys are able to detect them only in very small sky areas. Since these objects have low space densities, deep and wide surveys are necessary to obtain statistically relevant results about them. Euclid will be potentially capable of delivering the required information, but, given the lack of spectroscopic features at these distances within its bands, it is still unclear if it will be possible to identify and characterize these objects. The goal of this work is to assess the capability of Euclid, together with ancillary optical and near-infrared data, to identify these distant, dusty and massive galaxies, based on broadband photometry. We used a gradient-boosting algorithm to predict both the redshift and spectral type of objects at high $z$. To perform such an analysis we make use of simulated photometric observations derived using the SPRITZ software. The gradient-boosting algorithm was found to be accurate in predicting both the redshift and spectral type of objects within the Euclid Deep Survey simulated catalog at $z>2$. In particular, we study the analog of HIEROs (i.e. sources with $H-[4.5]>2.25$), combining Euclid and Spitzer data at the depth of the Deep Fields. We found that the dusty population at $3\lesssim z\lesssim 7$ is well identified, with a redshift RMS and OLF of only $0.55$ and $8.5\%$ ($H_E\leq26$), respectively. Our findings suggest that with Euclid we will obtain meaningful insights into the role of massive and dusty galaxies in the cosmic star-formation rate over time

Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees

International audienceDusty, distant, massive ($M_*\gtrsim 10^{11}\,\rm M_\odot$) galaxies are usually found to show a remarkable star-formation activity, contributing on the order of $25\%$ of the cosmic star-formation rate density at $z\approx3$--$5$, and up to $30\%$ at $z\sim7$ from ALMA observations. Nonetheless, they are elusive in classical optical surveys, and current near-infrared surveys are able to detect them only in very small sky areas. Since these objects have low space densities, deep and wide surveys are necessary to obtain statistically relevant results about them. Euclid will be potentially capable of delivering the required information, but, given the lack of spectroscopic features at these distances within its bands, it is still unclear if it will be possible to identify and characterize these objects. The goal of this work is to assess the capability of Euclid, together with ancillary optical and near-infrared data, to identify these distant, dusty and massive galaxies, based on broadband photometry. We used a gradient-boosting algorithm to predict both the redshift and spectral type of objects at high $z$. To perform such an analysis we make use of simulated photometric observations derived using the SPRITZ software. The gradient-boosting algorithm was found to be accurate in predicting both the redshift and spectral type of objects within the Euclid Deep Survey simulated catalog at $z>2$. In particular, we study the analog of HIEROs (i.e. sources with $H-[4.5]>2.25$), combining Euclid and Spitzer data at the depth of the Deep Fields. We found that the dusty population at $3\lesssim z\lesssim 7$ is well identified, with a redshift RMS and OLF of only $0.55$ and $8.5\%$ ($H_E\leq26$), respectively. Our findings suggest that with Euclid we will obtain meaningful insights into the role of massive and dusty galaxies in the cosmic star-formation rate over time

Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees

International audienceDusty, distant, massive ($M_*\gtrsim 10^{11}\,\rm M_\odot$) galaxies are usually found to show a remarkable star-formation activity, contributing on the order of $25\%$ of the cosmic star-formation rate density at $z\approx3$--$5$, and up to $30\%$ at $z\sim7$ from ALMA observations. Nonetheless, they are elusive in classical optical surveys, and current near-infrared surveys are able to detect them only in very small sky areas. Since these objects have low space densities, deep and wide surveys are necessary to obtain statistically relevant results about them. Euclid will be potentially capable of delivering the required information, but, given the lack of spectroscopic features at these distances within its bands, it is still unclear if it will be possible to identify and characterize these objects. The goal of this work is to assess the capability of Euclid, together with ancillary optical and near-infrared data, to identify these distant, dusty and massive galaxies, based on broadband photometry. We used a gradient-boosting algorithm to predict both the redshift and spectral type of objects at high $z$. To perform such an analysis we make use of simulated photometric observations derived using the SPRITZ software. The gradient-boosting algorithm was found to be accurate in predicting both the redshift and spectral type of objects within the Euclid Deep Survey simulated catalog at $z>2$. In particular, we study the analog of HIEROs (i.e. sources with $H-[4.5]>2.25$), combining Euclid and Spitzer data at the depth of the Deep Fields. We found that the dusty population at $3\lesssim z\lesssim 7$ is well identified, with a redshift RMS and OLF of only $0.55$ and $8.5\%$ ($H_E\leq26$), respectively. Our findings suggest that with Euclid we will obtain meaningful insights into the role of massive and dusty galaxies in the cosmic star-formation rate over time

Euclid: Early Release Observations -- Globular clusters in the Fornax galaxy cluster, from dwarf galaxies to the intracluster field

International audienceWe present an analysis of Euclid observations of a 0.5 deg$^2$ field in the central region of the Fornax galaxy cluster that were acquired during the performance verification phase. With these data, we investigate the potential of Euclid for identifying GCs at 20 Mpc, and validate the search methods using artificial GCs and known GCs within the field from the literature. Our analysis of artificial GCs injected into the data shows that Euclid's data in $I_{\rm E}$ band is 80% complete at about $I_{\rm E} \sim 26.0$ mag ($M_{V\rm } \sim -5.0$ mag), and resolves GCs as small as $r_{\rm h} = 2.5$ pc. In the $I_{\rm E}$ band, we detect more than 95% of the known GCs from previous spectroscopic surveys and GC candidates of the ACS Fornax Cluster Survey, of which more than 80% are resolved. We identify more than 5000 new GC candidates within the field of view down to $I_{\rm E}$ mag, about 1.5 mag fainter than the typical GC luminosity function turn-over magnitude, and investigate their spatial distribution within the intracluster field. We then focus on the GC candidates around dwarf galaxies and investigate their numbers, stacked luminosity distribution and stacked radial distribution. While the overall GC properties are consistent with those in the literature, an interesting over-representation of relatively bright candidates is found within a small number of relatively GC-rich dwarf galaxies. Our work confirms the capabilities of Euclid data in detecting GCs and separating them from foreground and background contaminants at a distance of 20 Mpc, particularly for low-GC count systems such as dwarf galaxies